Search Results for "frame analysis"

The software package 'relax' is designed for the study of molecular dynamics through the analysis of experimental NMR data. Organic molecules, proteins, RNA, DNA, sugars, and other biomolecules are all supported. It supports exponential curve fitting for the calculation of the R1 and R2 relaxation rates, calculation of the NOE, reduced spectral density mapping, the Lipari and Szabo model-free analysis, study of domain motions via the N-state model and frame order dynamics theories using anisotropic NMR parameters such as RDCs and PCSs, the investigation of stereochemistry in dynamic ensembles, and the analysis of relaxation dispersion data.

Feather is a fast, interoperable binary data frame storage format designed for efficient data exchange between analysis tools. It provides columnar serialization for data frames, making read and write operations faster than many text-based formats. The project was built to make sharing data across languages such as Python and R easier. Feather is powered by the Apache Arrow columnar memory specification, which helps it represent numeric, string, categorical, date, timestamp, boolean, and binary data efficiently. ...

test_gui is a modular tool for pnCCD data handling. It uses IDL type files (later 'frame' files). It plots and calculates different parameters related to XRF and XRD. A series of modules are attached for fitting and visualization. Test version 1 of this tool will be updated based on users needs.

CANStream is a .NET application intended to be used for CAN (Controller Area Network) bus communication development, testing and validation. CANStream allows to extensively test any system using CAN communication by sending and receiving CAN frames. Thanks to its powerful built-in mathematical expression evaluator, CANStream can also behave as a real control system feeding back the test device or commanding a third party device with context sensible data. Extended data logging and data...

Massively parallel sequencing of cDNA reverse transcribed from RNA (RNASeq) provides an accurate estimate of the quantity and composition of mRNAs. To characterize the transcriptome through the analysis of RNA-seq data, we developed PRADA. PRADA focuses on the processing and analysis of gene expression estimates, supervised and unsupervised gene fusion identification, and supervised intragenic deletion identification. PRADA currently supports 7 modules to process and identify abnormalities from RNAseq data: preprocess: Generates aligned and recalibrated BAM files. ...